Event listings, ticket prices and seat availability collected often enough to be useful - inventory on a popular show moves within minutes, not days.
Ticketing Platforms
Promoters and Venues
Artists and Management
Resale Marketplaces
Travel and Hospitality Companies
Sponsorship Agencies
Market Research Firms
Event Discovery Apps
Rights Holders and Anti-Touting Teams
Investment Analysts
Developers
Customers worldwide
Pages extracted
Hours saved for our clients
A ticket page is not a catalog page. Inventory and price on a popular show change within minutes of going on sale, and the interesting question is usually the gap between the primary price and what the same seat costs on resale. Related: travel and hospitality data.
Track the face value against the resale price for the same event and seating category to measure markup as it moves.
Watch availability by section over time to see how fast a show sells and where it stalls.
Capture price changes on the same seats over the sale period, which is the only way to see demand pricing in action.
Build a complete calendar for a city or genre from several platforms at once, deduplicated by venue and date.
Follow announcements to see which artists are touring where, and which venues and promoters they work with.
Spot resale listings that appear before general sale or above the permitted markup, where local rules cap it.
Large events move hotel and flight demand; the event calendar is a leading indicator for revenue management.
Every price row is stamped with the moment it was collected, because a ticket price without a timestamp is not a fact about anything.
Expertly customized web scraping services at a fraction of the cost of building and running collection in-house.
€199 / one-time
setup fee - included
€169 / mo
setup fee €499
€229 / mo
setup fee €499
€349 / mo
setup fee €499
€549 / mo
setup fee €799
Monitoring of real estate listings on funda.nl, pararius.com, rentberry.com, rentola.com, and zimmo.be to support the growth of a European property portal.
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Daily detection of new private property listings in Switzerland on Homegate.ch and ImmoScout24.ch, giving the agency first access to high-value leads.
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Daily monitoring of car listings on car.gr and autoscout24.com, collecting full technical specifications to support a European auto dealer.
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Scraping residential listings from Immobilienscout24.de in Germany and Mallorca, including complete data and resized images.
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Scraping supplement products from iHerb.com with full details, including descriptions and packaging variations.
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Weekly scraping of new real estate listings from PropertyGuru.com.my with full property and agent details.
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On-sale windows are collected at minute level, long-lead listings daily. One schedule for everything either misses the story or wastes the budget.
The same show is listed differently everywhere. We match on venue, date and artist so primary and resale prices line up on one row.
Headline price and total at checkout are different numbers, and the gap is often the whole point of the analysis.
You pay for the dataset, not for proxies, browser farms and the engineering time to keep them alive.
We watch the platforms for layout changes and fix collectors before your next on-sale.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
It depends on the moment. During an on-sale window minute-level collection is justified; for events months out, daily is plenty. We set the cadence per event rather than per platform.
Yes, and that is the most common brief. It requires matching the event across platforms on venue, date and artist, then aligning seating categories, which differ in naming between sites.
Where they are shown. Headline price and checkout total often differ substantially, so both are collected as separate fields rather than one blended number.
No. We collect published listing data. Automated purchasing is a different activity, it is restricted or illegal in several markets, and it is not a service we offer.
Yes, by collecting several platforms and deduplicating on venue, date and artist. No single source has everything, and the overlap between them is large but never complete.
CSV, Excel, JSON, JSONLines or XML, delivered over FTP, SFTP, Amazon S3, Google Cloud Storage, Dropbox, Google Drive or email. We can also write directly into your database.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582
